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Video Panoptic Segmentation (VPS) aims at assigning a class label to each pixel, uniquely segmenting and identifying all object instances consistently across all frames.
Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
Object-centric representation learning from unlabeled videos
Ruohan Gao, Dinesh Jayaraman, and Kristen Grauman · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
Earlier work this paper cites.
Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
Earlier work this paper cites.
Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Earlier work this paper cites.
Flownet 2.0: Evolution of optical flow estimation with deep networks
Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, and Thomas Brox · 2017
Earlier work this paper cites.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
Earlier work this paper cites.
The mapillary vistas dataset for semantic understanding of street scenes
Gerhard Neuhold, Tobias Ollmann, Samuel Rota Bulo, and Peter Kontschieder · 2017
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Playing for benchmarks
Stephan R Richter, Zeeshan Hayder, and Vladlen Koltun · 2017
Earlier work this paper cites.
Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Weakly-and semi-supervised panoptic segmentation
Qizhu Li, Anurag Arnab, and Philip HS Torr · 2018
Earlier work this paper cites.
Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
Earlier work this paper cites.
Yolact: Real-time instance segmentation
Daniel Bolya, Chong Zhou, Fanyi Xiao, and Yong Jae Lee · 2019
Earlier work this paper cites.
Mmdetection: Open mmlab detection toolbox and benchmark
Kai Chen, Jiaqi Wang, Jiangmiao Pang, Yuhang Cao, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jiarui Xu, et al · 2019
Earlier work this paper cites.
Autoaugment: Learning augmentation strategies from data
Ekin D Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V Le · 2019
Cited alongside, same era.
Genesis: Generative scene inference and sampling with object-centric latent representations
Martin Engelcke, Adam R Kosiorek, Oiwi Parker Jones, and Ingmar Posner · 2019
Cited alongside, same era.
Panoptic feature pyramid networks
Alexander Kirillov, Ross Girshick, Kaiming He, and Piotr Dollár · 2019
Cited alongside, same era.
Panoptic segmentation
Alexander Kirillov, Kaiming He, Ross Girshick, Carsten Rother, and Piotr Dollár · 2019
Cited alongside, same era.
Upsnet: A unified panoptic segmentation network
Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, and Raquel Urtasun · 2019
Cited alongside, same era.
Video instance segmentation
Linjie Yang, Yuchen Fan, and Ning Xu · 2019
Conditional convolutions for instance segmentation
Zhi Tian, Chunhua Shen, and Hao Chen · 2020
Later among the works it cites.
Towards interpretable semantic segmentation via gradient-weighted class activation mapping
Kira Vinogradova, Alexandr Dibrov, and Gene Myers · 2020
Later among the works it cites.
Siam r-cnn: Visual tracking by re-detection
Paul Voigtlaender, Jonathon Luiten, Philip HS Torr, and Bastian Leibe · 2020
Later among the works it cites.
Towards real-time multi-object tracking
Zhongdao Wang, Liang Zheng, Yixuan Liu, Yali Li, and Shengjin Wang · 2020
Later among the works it cites.
Syntax-aware action targeting for video captioning
Qi Zheng, Chaoyue Wang, and Dacheng Tao · 2020
Later among the works it cites.
Tracking objects as points
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
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Cited alongside, same era.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Cited alongside, same era.
Naive-student: Leveraging semi-supervised learning in video sequences for urban scene segmentation
Liang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng, Maxwell D Collins, Ekin D Cubuk, Barret Zoph, Hartwig Adam, and Jonathon Shlens · 2020
Cited alongside, same era.
Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation
Bowen Cheng, Maxwell D Collins, Yukun Zhu, Ting Liu, Thomas S Huang, Hartwig Adam, and Liang-Chieh Chen · 2020
Cited alongside, same era.
Video panoptic segmentation
Dahun Kim, Sanghyun Woo, Joon-Young Lee, and In So Kweon · 2020
Cited alongside, same era.
Learning instance occlusion for panoptic segmentation
Justin Lazarow, Kwonjoon Lee, Kunyu Shi, and Zhuowen Tu · 2020
Cited alongside, same era.
Centermask: Real-time anchor-free instance segmentation
Youngwan Lee and Jongyoul Park · 2020
Cited alongside, same era.
Later among the works it cites.
Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
Later among the works it cites.
Recurrent attention models with object-centric capsule representation for multi-object recognition
Hossein Adeli, Seoyoung Ahn, and Gregory Zelinsky · 2021
Closest in time.
Per-pixel classification is not all you need for semantic segmentation
Bowen Cheng, Alexander G Schwing, and Alexander Kirillov · 2021
Closest in time.
Sg-net: Spatial granularity network for one-stage video instance segmentation
Dongfang Liu, Yiming Cui, Wenbo Tan, and Yingjie Chen · 2021
Closest in time.
Semantic tracklets: An object-centric representation for visual multi-agent reinforcement learning
Iou-Jen Liu, Zhongzheng Ren, Raymond A Yeh, and Alexander G Schwing · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Bridge to answer: Structure-aware graph interaction network for video question answering
Jungin Park, Jiyoung Lee, and Kwanghoon Sohn · 2021
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Detectors: Detecting objects with recursive feature pyramid and switchable atrous convolution
Siyuan Qiao, Liang-Chieh Chen, and Alan Yuille · 2021
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Max-deeplab: End-to-end panoptic segmentation with mask transformers
Huiyu Wang, Yukun Zhu, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen · 2021
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End-to-end video instance segmentation with transformers
Yuqing Wang, Zhaoliang Xu, Xinlong Wang, Chunhua Shen, Baoshan Cheng, Hao Shen, and Huaxia Xia · 2021
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Learning to associate every segment for video panoptic segmentation
Sanghyun Woo, Dahun Kim, Joon-Young Lee, and In So Kweon · 2021
Closest in time.